Images with sparse information are images where electromagnetic radiation or particle radiation is only impacting on a limited number of pixels on an imaging system, leaving a dark background (no radiation) for the remainder of the pixels.
An objective of imaging systems for reading out images with sparse information is to obtain the positions of the impacted pixels and the intensity of the impact.
Such imaging systems may for example be applied for X-ray imaging, for X-ray photon counting, for CT, for gamma ray detection with spatial resolution, for a neutron camera, for high energy physics, or for electron microscopy.
These imaging systems suffer from problems when the impact rate of the particles/photons is so high that the imaging system cannot be read out fast enough to grasp each individual impact.
Prior art solutions address this problem by limiting the flux or fluence (particles/area/time) or by integrating the signal of a pixel over time. Thereby, multiple impacts on the same pixel are integrated such that all impacts are grasped. However, individual impacts within the same integration period cannot be distinguished anymore. Thus place/shape/amplitude information of the constituting impacts is lost. These solutions result in a worse position resolution and in an increased noise level.
In more advanced prior art solutions this problem is addressed by using smart pixels. Smart pixels have integrated features which allow them to count events in the pixels and which even allow them to execute operators in the pixels or in a local group of pixels to obtain sufficient resolution. An example thereof is disclosed in US2010/0213353 A1 (Analog photon counting). A problem of these pixels is, however, that they have a large size (e.g. >30 μm) compared to regular pixels. Therefore they cannot be used in a high resolution imager.